Present work is aimed to develop a simple, sensitive, robust and reliable HPLC method for routine quality control of epirubicin (EPI) in bulk drug, marketed injections and polymeric nanoparticles. Separation was carried out by C18 column. Isocratic elution was carried out using mobile phase A: 0.16% o-phosphoric acid solution, B: acetonitrile and methanol mixture (80:20, v/v) in the ratio of 60:40 (A: B) while the flow rate was maintained at 1mL/min. Analyses were performed at 233.5 nm using PDA detector. Excellent linear relationship was observed between peak-area versus drug concentration in the range of 1.0-100.0 μg/mL (r2, 0.999). Developed method was found to be sensitive (Limits of detection and quantification were found to be ~8 ng/mL and ~25 ng/mL, respectively), precise (RSD <1.0%, for repeatability and <2.0% for intermediate precision, within acceptable ranges of precision), accurate (recovery in different dosage form, 94.65 -100.26%, within acceptable range, 80-120%), specific and robust (% RSD <2, for system suitability parameters). Stress-induced degradation studies demonstrated that method can suitability be applied in the presence of degradants. Developed method has been successfully applied for the determination of entrapment efficiency, drug loading, in vitro release profile, in vitro permeation studies as well as stability assessment of polymeric nanoparticles.

ABSTRACT The present study aimed at comparing predictive performance of some data mining algorithms (CART, CHAID, Exhaustive CHAID, MARS, MLP, and RBF) in biometrical data of Mengali rams. To compare the predictive capability of the algorithms, the biometrical data regarding body (body length, withers height, and heart girth) and testicular (testicular length, scrotal length, and scrotal circumference) measurements of Mengali rams in predicting live body weight were evaluated by most goodness of fit criteria. In addition, age was considered as a continuous independent variable. In this context, MARS data mining algorithm was used for the first time to predict body weight in two forms, without (MARS_1) and with interaction (MARS_2) terms. The superiority order in the predictive accuracy of the algorithms was found as CART > CHAID ≈ Exhaustive CHAID > MARS_2 > MARS_1 > RBF > MLP. Moreover, all tested algorithms provided a strong predictive accuracy for estimating body weight. However, MARS is the only algorithm that generated a prediction equation for body weight. Therefore, it is hoped that the available results might present a valuable contribution in terms of predicting body weight and describing the relationship between the body weight and body and testicular measurements in revealing breed standards and the conservation of indigenous gene sources for Mengali sheep breeding. Therefore, it will be possible to perform more profitable and productive sheep production. Use of data mining algorithms is useful for revealing the relationship between body weight and testicular traits in describing breed standards of Mengali sheep.

In this contribution we present an overview on the relation between the complex structure of ionic liquids (ILs) and its impact in the field of surface science. The results herein described result mainly from modeling and simulation work carried out at Centro de Química Estrutural, Universidade de Lisboa, complemented in some cases by experimental results obtained at Instituto de Tecnologia Química e Biológica, Universidade Nova de Lisboa or elsewhere. The overview starts with the description of nano-segregation and self-aggregation phenomena experienced by pure ionic liquids in bulk phases (bi-continuous structures in the isotropic liquid or the formation of liquid-crystal phases). This is followed by the analysis of IL self-aggregation in molecular solvent solutions (micelle or gel formation). The second part of the overview is devoted to the study of the structuration of ILs at the IL/vacuum, IL/liquid or IL/solid interfaces. The final part deals with thin IL films stabilized between air/solid, air/liquid or solid/solid boundaries.

A program has been developed to calculate enthalpies at the salient points (later referred to as stations) of a combined power and cooling cycle provided pressure, temperature, mixture concentration and condition are known at these points. The ammonia-water mixture, which is taken as the working fluid, may be at one of the following seven conditions namely, superheated vapour mixture, mixture of superheated component of ammonia and pseudo vapour component of water, saturated vapour mixture, wet vapour mixture, saturated liquid mixture, mixture of subcooled water and pseudo liquid ammonia and subcooled mixture of sub-cooled components of ammonia and water. The mixture boiling-point temperature and dew-point temperature, needed to establish the condition of the working fluid, are functions of absolute pressure, critical pressure and critical temperature of the mixture; later two depend on the mixture concentration and the corresponding critical values of water at the given station. Using typical values of the variables as listed above, enthalpies at all stations are predicted. The predicted enthalpies are close (within 3%) to those available in the literature except at two stations where the mixture was weak in ammonia and its temperature was either in the near vicinity of the mixture boiling-point temperature or below the saturation temperature of pure ammonia at the concerned pressure. Using the predicted values of enthalpies, thermal efficiency of the combined power and cooling cycle has been calculated.